Our ability to see color has long been a central issue for vision research. Color vision is important for most people's quality of life, and the deterioration of color vision often indicates serious health-related vision problems. Color, however, is a complex perception that depends not only on the wavelength of a light, but also on the context in which the light is presented: for example, for an observer with no color vision deficits, a white disk looks green when surrounded by a red ring. Explanations for the effects of context typically posit that the neural response to the target light (in this case, the white disk) is modified by the neural response to the contextual light (in this case, the red ring). Such explanations have been valuable for understanding many aspects of the visual brain but generally do not attempt to account for the fact that objects can be described in terms of both their color and their color contrast (a red disk surrounded by a white ring appears "red with high contrast," but a red disk surrounded by a pink ring appears "red with low contrast"). Over the past few years, the Shapiro laboratory has developed new techniques to show that the visual response to color contrast can be measured separately from the visual response to color. The results have led to the development of a computational model in which the visual system carries two different classes of signal: a signed (or non-rectified) response that corresponds to the neural channels typically studied in color vision experiments, and an unsigned (or rectified) response that encodes color contrast. The experiments described in Specific Aims 1 and 2 use the temporal and spatial signatures of the rectified and non-rectified responses to understand fundamental characteristics of those responses at threshold and super-threshold levels. The experiments described in Specific Aim 3 examine a ramification of the model, with respect to brightness perception: i.e., the hypothesis that the parts of the human visual system that encode brightness act like an adaptive high-pass filter that removes low spatial frequency content from the visual scene, with the cutoff frequency determined by the image content. My proposed model is of interest to many Vision Science researchers. Specific aim 4 shows specific collaborations that have clinical applications that can be developed as a consequence of this R15 award. PUBLIC HEALTH RELEVANCE: Color vision is important for most people's quality of life, and the deterioration of color vision often indicates serious health-related vision problems. The research in this proposal seeks to understand aspects of color vision related to a model that proposes separable neural processes for color and color contrast, developed by Shapiro (2008). The techniques described in this proposal are new and can be applied to the study of Congenital Stationary Night Blindness, and visual decline that occurs as a result of aging.